A Validation Study of The Greek Version of The Toronto Empathy Questionnaire In Medical Students And A Measurement of Their Empathy
Bibliographic record
Abstract
Abstract Aims and objectives: Empathy is an important key driver of any therapeutic relationship. It is beneficial not only to the patients, but also to physicians. Enhancing physician’s empathy should be an important goal of medical education. As there is a literature gap regarding the topic of empathy among medical students in Greece, this study aims to contribute to filling this gap.Methods: A cross-sectional study was conducted. The (validated in Greece) Greek version of Toronto 52‐item empathy 6-point Likert-scale was administered to all the medical students in the Aristotle University of Thessaloniki, in Greece. In addition, participants were asked to provide information regarding their socio-demographics. A demographic comparison was conducted.Results: The preliminary validation of the Greek version of the Toronto Composite Empathy Scale (TCES) demonstrated acceptable validity and reliability among medical students and could be further tested in larger samples of medical students. The overall reliability analysis of the TCES questionnaire is high (Cronbach's α = 0.895, Sig. from Hotelling’s T-Squared Test < 0.000). The mean total score of empathy showed that students have a moderately high empathy. The 52‐item TCES, 26 for the personal (Per) setting and another 26 for professional (Pro) life, equally divided into cognitive (Cog) and emotional (Emo) empathy in each case. It was found that there is a statistically significant difference in means between the Per-Cog and Per-Emo settings (Sig < 0.001), the Pro-Cog and Pro-Emo (Sig < 0.001), the Per-Cog and Pro-Cog (Sig = 0.004), and the Per-Emo and Pro-Emo (Sig < 0.001). Females had significantly higher empathy scores (mean score 208.04) than males (mean score 192.5) on the Per-Cognitive, Per-Emo and Pro-Emo subscales. Furthermore, a positive correlation was found between empathy and factors such as love for animals, interest in medical ethics, belief in God, having an ill person in the family, class year or carrier intention. Conclusions: The Toronto Composite Empathy Scale (TCES) is applicable to medical students. For the most part our findings were consistent with previous literature. However, we identified some nuances that might draw researchers’ attention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".